Post-Translational Modification of p62: Roles and Regulations in Autophagy
Bibliographic record
Abstract
Autophagy is a highly conserved cellular process that plays a crucial role in maintaining cellular homeostasis by degrading damaged organelles, misfolded proteins, and other cellular components. p62/SQSTM1 functions as a selective autophagy receptor by binding polyubiquitinated cargo through its UBA domain and linking it to microtubule-associated protein light chain 3 (LC3)-decorated autophagosomes. Moreover, p62 acts as a signaling hub and is essential in response to various stressors, including nutrient deprivation and oxidative stress. Post-translational modifications (PTMs) critically regulate p62's multifaceted roles, controlling p62's phase separation, cargo recruitment, signaling interactions, and autophagic degradation efficiency. The dysregulation of p62 PTMs is closely related to the occurrence and development of human diseases, particularly neurodegenerative disorders and certain cancers. This review summarizes the main PTM events of p62 discovered to date that influence the autophagy process, including phosphorylation, acetylation, ubiquitination, and S-acylation, as well as their known contributions to protein aggregation and disease. The PTMs of p62 dynamically regulate autophagy, protein aggregation, and cellular signaling, underscoring its importance as a potential therapeutic target and biomarker for these diseases.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".